On the Communication Pathways between the Central Pacemaker and Peripheral Oscillators
Bibliographic record
Abstract
Circadian rhythms are regulated by clocks located in specific structures of the CNS, such as the suprachiasmatic nucleus (SCN) in mammals, and by peripheral oscillators present in various other tissues. The expression of essential clock genes oscillates both in the SCN and in peripheral pacemakers. Peripheral tissues in the fly and in the fish are directly photoreceptive. In particular, we have established the Z3 embryonic zebrafish cell line that recapitulates the dynamic light-dependent regulation of the vertebrate clock in vitro. In mammals the synchronization to daily light cycles involves neural connections from a subset of light-sensitive receptor-containing retinal ganglion cells. Humoral and/or hormonal signals originating from the SCN are thought to provide timing cues to peripheral clocks. However, alternative routes exist, as some peripheral clocks in mammals can be specifically entrained in a SCN-independent manner by restricted feeding regimes. Thus, not all peripheral tissues are equal in circadian rhythmicity. Testis, for example, displays no intrinsic circadian rhythmicity and the molecular mechanisms of clock gene activation in male germ cells appear to differ from other tissues. The study of the connecting routes that link the SCN to peripheral tissues is likely to reveal signalling pathways of fundamental physiological significance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".